1. Technical Field
This invention relates to the field of natural language understanding, and more particularly, to a method of processing dual tone multi-frequency signals in a conversational natural language system.
2. Description of the Related Art
Natural language understanding (NLU) systems enable computers to understand and extract information from human written or spoken language. Such systems can function in a complimentary manner with a variety of other computer applications where there exists a need to understand human language. NLU systems can extract relevant information contained within text and then supply this information to another application program or system for purposes such as booking flight reservations, finding documents, or summarizing text.
Currently within the art, many NLU systems are implemented as directed dialog systems. Directed dialog NLU systems typically prompt or instruct a user as to the proper form of an immediate user response. For example, a directed dialog NLU system can instruct a user as follows “Press or say 1 for choice A, Press or say 2 for choice B”. By instructing the user as to the proper format for an immediate user response, the NLU system can expect a particular type of response such as speech input or keypad input. Accordingly, the NLU system can process that user response more accurately and function more efficiently.
For an NLU system to be capable of accepting keypad input from a telephone, known as dual tone multi-frequency (DTMF) signaling, the NLU system must be DTMF enabled. Specifically, the NLU system requires programming for converting the DTMF signals into corresponding numeric values. Once converted into numeric values, the meaning of the resulting digit strings need not be determined and can be passed directly to the part of the NLU system responsible for determining a user action and the arguments of that action. In other words, the digit string need not be pre-processed by the sub-systems of the NLU system responsible for meaning extraction as would be the case had the user uttered a complete sentence containing spoken numbers. In conventional NLU system implementations, however, bypassing the pre-processing sub-systems responsible for meaning extraction, i.e., parsing input text and classing that text, can be complex.
For example, an NLU system and its constituent parts, such as a speech recognition system, can be implemented within an interactive voice response unit (IVR) designed to work cooperatively with a telephone switching system. An IVR unit, as is known in the art, can accept a combination of voice telephone input and DTMF input from a keypad. Each telephony hardware manufacturer, however, typically has a proprietary interface for dealing with hardware and software components requiring a custom solution for each manufacturer's equipment. Moreover, at each point in the NLU system where DTMF signals can be received, the NLU system's pre-processing systems must be bypassed. Thus, special programming must be included in each location in the NLU system where DTMF input is acceptable. Notably, this solution can be complex, though system designers can plan for the complexity in the case of a directed dialog NLU system by expressly asking a user to speak or to press a key. Thus, system designers can limit the number of response points where a user can respond using DTMF signaling.
As NLU systems advance, however, and move away from directed dialog systems toward more conversational systems, the NLU system must be able to receive input in a variety of formats. Because conversational NLU systems do not give users the directed and immediate guidance associated with directed dialog NLU systems, a user can unexpectedly press a key to make a selection rather than speak the selection. For a conversational NLU system to receive and process both DTMF and speech at any response point, the NLU system would have to incorporate the special bypass programming at each response point. As a result, a conversational NLU system implemented in this manner would be prohibitively complex.